Artificial neural network regression model to predict flue gas temperature and emissions with the spectral norm of flame image

Author:

Golgiyaz SedatORCID,Talu Muhammed Fatih,Onat Cem

Funder

The Scientific and Technological Research Council of Turkey

Publisher

Elsevier BV

Subject

Organic Chemistry,Energy Engineering and Power Technology,Fuel Technology,General Chemical Engineering

Reference33 articles.

1. Conti J, Holtberg P, Diefenderfer J, LaRose A, Turnure JT, Westfall L. International Energy Outlook 2016 With Projections to 2040; May 2016.

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3. Golgiyaz S, Talu MF, Onat C. Estimation of excess air coefficient for automated feed coal burners with image-based gauss model. In: International conference on artificial intelligence and data processing IDAP’16; 2016. p. 528–31.

4. Vector and matrix norms;Blackledget;Digit Signal Process,2013

5. Coal flame characterization by means of digital image processing in a semi-industrial scale PF swirl burner;González-Cencerrado;Appl Energy,2012

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